When working interactively in a MATLAB® session, you can offload work to a MATLAB worker session to run as a batch job. The command to perform this job is asynchronous, which means that your client MATLAB session is not blocked, and you can continue your own interactive session while the MATLAB worker is busy evaluating your code. You can also create a pool of workers for your batch job. The workers can run either on the same machine as the client, or if using MATLAB Parallel Server™, on a remote cluster machine.
Use batch to offload work from your MATLAB session to run in the background.
Run functions as batch jobs and control options, such as accessing files from workers.
Find out how to pass data and code to and from the workers.
The random number generation functions
randn behave differently for parallel calculations compared to your
Send Deep Learning Batch Job to Cluster (Deep Learning Toolbox)
This example shows how to send deep learning training batch jobs to a cluster so that you can continue working or close MATLAB during training.
Manage your jobs using the Job Monitor